{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Riskfolio-Lib Tutorial:\n",
    "<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__\n",
    "<br>__[Orenji](https://www.orenj-i.net)__\n",
    "<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__\n",
    "<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__\n",
    "<a href='https://ko-fi.com/B0B833SXD' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=2' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a> \n",
    "\n",
    "## Tutorial 7: Index Tracking/Replicating Portfolios\n",
    "\n",
    "## 1. Downloading the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  26 of 26 completed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "yf.pdr_override()\n",
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "\n",
    "# Date range\n",
    "start = '2016-01-01'\n",
    "end = '2019-12-30'\n",
    "\n",
    "# Tickers of assets\n",
    "assets = ['JCI', 'TGT', 'CMCSA', 'CPB', 'MO', 'APA', 'MMC', 'JPM',\n",
    "          'ZION', 'PSA', 'BAX', 'BMY', 'LUV', 'PCAR', 'TXT', 'TMO',\n",
    "          'DE', 'MSFT', 'HPQ', 'SEE', 'VZ', 'CNP', 'NI', 'T', 'BA']\n",
    "assets.sort()\n",
    "\n",
    "market_index = ['^GSPC']\n",
    "\n",
    "all_assets = assets + market_index\n",
    "all_assets.sort()\n",
    "\n",
    "# Downloading data\n",
    "data = yf.download(all_assets, start = start, end = end)\n",
    "data = data.loc[:,('Adj Close', slice(None))]\n",
    "data.columns = all_assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "      <th>^GSPC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>-2.0257%</td>\n",
       "      <td>0.4057%</td>\n",
       "      <td>0.4035%</td>\n",
       "      <td>1.9693%</td>\n",
       "      <td>0.0180%</td>\n",
       "      <td>0.9305%</td>\n",
       "      <td>0.3678%</td>\n",
       "      <td>0.5783%</td>\n",
       "      <td>0.9483%</td>\n",
       "      <td>-1.1954%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>2.8236%</td>\n",
       "      <td>0.9758%</td>\n",
       "      <td>0.6987%</td>\n",
       "      <td>1.7539%</td>\n",
       "      <td>-0.1730%</td>\n",
       "      <td>0.2410%</td>\n",
       "      <td>1.3734%</td>\n",
       "      <td>-1.0857%</td>\n",
       "      <td>0.2012%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>-11.4863%</td>\n",
       "      <td>-1.5879%</td>\n",
       "      <td>0.2412%</td>\n",
       "      <td>-1.7557%</td>\n",
       "      <td>-0.7727%</td>\n",
       "      <td>-1.2473%</td>\n",
       "      <td>-0.1736%</td>\n",
       "      <td>-1.1239%</td>\n",
       "      <td>-3.5867%</td>\n",
       "      <td>-0.9551%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>0.1592%</td>\n",
       "      <td>-1.5646%</td>\n",
       "      <td>-0.1466%</td>\n",
       "      <td>-1.0155%</td>\n",
       "      <td>-0.7653%</td>\n",
       "      <td>-3.0048%</td>\n",
       "      <td>-0.9034%</td>\n",
       "      <td>-2.9145%</td>\n",
       "      <td>-1.3115%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>-5.1389%</td>\n",
       "      <td>-4.1922%</td>\n",
       "      <td>-1.6573%</td>\n",
       "      <td>-2.7699%</td>\n",
       "      <td>-1.1047%</td>\n",
       "      <td>-1.9769%</td>\n",
       "      <td>-1.2207%</td>\n",
       "      <td>-0.8855%</td>\n",
       "      <td>-4.6059%</td>\n",
       "      <td>-2.5394%</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.0309%</td>\n",
       "      <td>-1.0410%</td>\n",
       "      <td>-3.1557%</td>\n",
       "      <td>-1.6148%</td>\n",
       "      <td>-0.2700%</td>\n",
       "      <td>-2.2845%</td>\n",
       "      <td>-2.0570%</td>\n",
       "      <td>-0.5492%</td>\n",
       "      <td>-3.0019%</td>\n",
       "      <td>-2.3700%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>0.2737%</td>\n",
       "      <td>-2.2705%</td>\n",
       "      <td>-1.6037%</td>\n",
       "      <td>-2.5425%</td>\n",
       "      <td>0.1099%</td>\n",
       "      <td>-0.2241%</td>\n",
       "      <td>0.5707%</td>\n",
       "      <td>-1.6402%</td>\n",
       "      <td>-1.7641%</td>\n",
       "      <td>-0.1649%</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.1366%</td>\n",
       "      <td>-0.7308%</td>\n",
       "      <td>-0.1448%</td>\n",
       "      <td>0.0895%</td>\n",
       "      <td>-3.3839%</td>\n",
       "      <td>-0.1117%</td>\n",
       "      <td>-1.1386%</td>\n",
       "      <td>-0.9719%</td>\n",
       "      <td>-1.1254%</td>\n",
       "      <td>-1.0838%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>-4.3384%</td>\n",
       "      <td>0.1693%</td>\n",
       "      <td>-1.6851%</td>\n",
       "      <td>-1.0215%</td>\n",
       "      <td>0.0915%</td>\n",
       "      <td>-1.1791%</td>\n",
       "      <td>0.5674%</td>\n",
       "      <td>0.5287%</td>\n",
       "      <td>0.6616%</td>\n",
       "      <td>0.0330%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9869%</td>\n",
       "      <td>-0.1450%</td>\n",
       "      <td>1.2224%</td>\n",
       "      <td>1.4570%</td>\n",
       "      <td>0.5367%</td>\n",
       "      <td>-0.4607%</td>\n",
       "      <td>0.5800%</td>\n",
       "      <td>-1.9918%</td>\n",
       "      <td>0.0853%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 APA       BA      BAX      BMY    CMCSA      CNP      CPB  \\\n",
       "Date                                                                         \n",
       "2016-01-05  -2.0257%  0.4057%  0.4035%  1.9693%  0.0180%  0.9305%  0.3678%   \n",
       "2016-01-06 -11.4863% -1.5879%  0.2412% -1.7557% -0.7727% -1.2473% -0.1736%   \n",
       "2016-01-07  -5.1389% -4.1922% -1.6573% -2.7699% -1.1047% -1.9769% -1.2207%   \n",
       "2016-01-08   0.2737% -2.2705% -1.6037% -2.5425%  0.1099% -0.2241%  0.5707%   \n",
       "2016-01-11  -4.3384%  0.1693% -1.6851% -1.0215%  0.0915% -1.1791%  0.5674%   \n",
       "\n",
       "                 DE      HPQ      JCI  ...     PCAR      PSA      SEE  \\\n",
       "Date                                   ...                              \n",
       "2016-01-05  0.5783%  0.9483% -1.1954%  ...  0.0212%  2.8236%  0.9758%   \n",
       "2016-01-06 -1.1239% -3.5867% -0.9551%  ...  0.0212%  0.1592% -1.5646%   \n",
       "2016-01-07 -0.8855% -4.6059% -2.5394%  ... -3.0309% -1.0410% -3.1557%   \n",
       "2016-01-08 -1.6402% -1.7641% -0.1649%  ... -1.1366% -0.7308% -0.1448%   \n",
       "2016-01-11  0.5287%  0.6616%  0.0330%  ...  0.0000%  0.9869% -0.1450%   \n",
       "\n",
       "                  T      TGT      TMO      TXT       VZ     ZION    ^GSPC  \n",
       "Date                                                                       \n",
       "2016-01-05  0.6987%  1.7539% -0.1730%  0.2410%  1.3734% -1.0857%  0.2012%  \n",
       "2016-01-06 -0.1466% -1.0155% -0.7653% -3.0048% -0.9034% -2.9145% -1.3115%  \n",
       "2016-01-07 -1.6148% -0.2700% -2.2845% -2.0570% -0.5492% -3.0019% -2.3700%  \n",
       "2016-01-08  0.0895% -3.3839% -0.1117% -1.1386% -0.9719% -1.1254% -1.0838%  \n",
       "2016-01-11  1.2224%  1.4570%  0.5367% -0.4607%  0.5800% -1.9918%  0.0853%  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating returns\n",
    "\n",
    "Y = data[all_assets].pct_change().dropna()\n",
    "\n",
    "display(Y.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Estimating Mean Variance Portfolios with Turnover Constraints\n",
    "\n",
    "### 2.1 Calculating the portfolio that maximizes Sharpe ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.1284%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.8717%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA     BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 9.0000% 9.0000% 0.0000% 2.1284% 9.0000% 0.0000% 7.8717%   \n",
       "\n",
       "            HPQ     JCI  ...      NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 9.0000% 0.0000% 0.0000% 0.0000% 0.0000% 9.0000%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 9.0000% 0.0000% 9.0000% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.Portfolio as pf\n",
    "\n",
    "# Building the portfolio object\n",
    "port = pf.Portfolio(returns=Y[assets])\n",
    "# Calculating optimum portfolio\n",
    "\n",
    "# Select method and estimate input parameters:\n",
    "\n",
    "method_mu='hist' # Method to estimate expected returns based on historical data.\n",
    "method_cov='hist' # Method to estimate covariance matrix based on historical data.\n",
    "\n",
    "port.assets_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)\n",
    "\n",
    "# Create Turnover Constraints\n",
    "\n",
    "port.allowTO = True # Allows to use Turnover Constraints\n",
    "port.turnover = 0.05 # Maximum deviation in absolute value respect to benchmark weights\n",
    "# By default benchweights is the equally weighted portfolio,\n",
    "# if you want to use a different benchmark weights, you must\n",
    "# specify a weights dataframe with assets names in columns\n",
    "#port.benchweights = weights # Use a dataframe\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "model='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "obj = 'Sharpe' # Objective function, could be MinRisk, MaxRet, Utility or Sharpe\n",
    "hist = True # Use historical scenarios for risk measures that depend on scenarios\n",
    "rf = 0 # Risk free rate\n",
    "l = 0 # Risk aversion factor, only useful when obj is 'Utility'\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.PlotFunctions as plf\n",
    "\n",
    "# Plotting the composition of the portfolio\n",
    "\n",
    "ax = plf.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                  height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.1781%</td>\n",
       "      <td>5.1969%</td>\n",
       "      <td>3.0387%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>4.8221%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.5881%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.8733%</td>\n",
       "      <td>6.9963%</td>\n",
       "      <td>4.5308%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.6036%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>2.7744%</td>\n",
       "      <td>3.2089%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>4.0378%</td>\n",
       "      <td>1.3301%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.5006%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.2040%</td>\n",
       "      <td>5.4665%</td>\n",
       "      <td>0.7526%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.2403%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>1.7359%</td>\n",
       "      <td>3.2037%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>3.7088%</td>\n",
       "      <td>1.8968%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0720%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.9722%</td>\n",
       "      <td>5.8474%</td>\n",
       "      <td>1.4536%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.7328%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.9325%</td>\n",
       "      <td>3.2001%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>3.4545%</td>\n",
       "      <td>2.3356%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.7411%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.7913%</td>\n",
       "      <td>6.1414%</td>\n",
       "      <td>1.9970%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.1145%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.1938%</td>\n",
       "      <td>3.1189%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>3.1843%</td>\n",
       "      <td>2.6998%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.3686%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.5739%</td>\n",
       "      <td>6.3868%</td>\n",
       "      <td>2.4304%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA     CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 7.1781% 5.1969% 3.0387% 9.0000% 4.8221% 0.0000% 0.0000%   \n",
       "1 0.0000% 1.6036% 9.0000% 2.7744% 3.2089% 9.0000% 4.0378% 1.3301% 0.0000%   \n",
       "2 0.0000% 2.2403% 9.0000% 1.7359% 3.2037% 9.0000% 3.7088% 1.8968% 0.0000%   \n",
       "3 0.0000% 2.7328% 9.0000% 0.9325% 3.2001% 9.0000% 3.4545% 2.3356% 0.0000%   \n",
       "4 0.0000% 3.1145% 9.0000% 0.1938% 3.1189% 9.0000% 3.1843% 2.6998% 0.0000%   \n",
       "\n",
       "      JCI  ...      NI    PCAR     PSA     SEE       T     TGT     TMO  \\\n",
       "0 3.5881%  ... 9.0000% 0.0000% 9.0000% 0.8733% 6.9963% 4.5308% 0.0000%   \n",
       "1 2.5006%  ... 9.0000% 0.0000% 9.0000% 0.0000% 6.2040% 5.4665% 0.7526%   \n",
       "2 2.0720%  ... 9.0000% 0.0000% 9.0000% 0.0000% 5.9722% 5.8474% 1.4536%   \n",
       "3 1.7411%  ... 9.0000% 0.0000% 9.0000% 0.0000% 5.7913% 6.1414% 1.9970%   \n",
       "4 1.3686%  ... 9.0000% 0.0000% 9.0000% 0.0000% 5.5739% 6.3868% 2.4304%   \n",
       "\n",
       "      TXT      VZ    ZION  \n",
       "0 0.0000% 9.0000% 0.0000%  \n",
       "1 0.0000% 9.0000% 0.0000%  \n",
       "2 0.0000% 9.0000% 0.0000%  \n",
       "3 0.0000% 9.0000% 0.0000%  \n",
       "4 0.0000% 9.0000% 0.0000%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the efficient frontier\n",
    "\n",
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "mu = port.mu # Expected returns\n",
    "cov = port.cov # Covariance matrix\n",
    "returns = port.returns # Returns of the assets\n",
    "\n",
    "ax = plf.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                       rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                       marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = plf.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Estimating Mean Variance Portfolios with Tracking Error Constraints\n",
    "\n",
    "### 3.1 Calculating the portfolio that maximizes Sharpe ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.1591%</td>\n",
       "      <td>11.5021%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.4806%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.8189%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.8260%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.1806%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.2717%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 6.1591% 11.5021% 0.0000% 0.0000% 8.4806% 0.0000% 3.8189%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 10.8260% 0.0000% 0.0000% 0.0000% 0.0000% 7.1806%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 0.0000% 0.0000% 4.2717% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.Portfolio as pf\n",
    "\n",
    "# Building the portfolio object\n",
    "port = pf.Portfolio(returns=Y[assets])\n",
    "# Calculating optimum portfolio\n",
    "\n",
    "# Select method and estimate input parameters:\n",
    "\n",
    "method_mu='hist' # Method to estimate expected returns based on historical data.\n",
    "method_cov='hist' # Method to estimate covariance matrix based on historical data.\n",
    "\n",
    "port.assets_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)\n",
    "\n",
    "# Create Tracking Error Constraints\n",
    "\n",
    "port.kindbench = False # True if you have benchmark weights, False if you have an index\n",
    "port.benchindex = Y[market_index] # Index Returns\n",
    "port.allowTE = True # Allows to use Tracking Error Constraints\n",
    "port.TE = 0.008 # Maximum Tracking Error respect to benchmark returns\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "model='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "obj = \"Sharpe\" # Objective function, could be MinRisk, MaxRet, Utility or Sharpe\n",
    "hist = True # Use historical scenarios for risk measures that depend on scenarios\n",
    "rf = 0 # Risk free rate\n",
    "l = 0 # Risk aversion factor, only useful when obj is 'Utility'\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.PlotFunctions as plf\n",
    "\n",
    "# Plotting the composition of the portfolio\n",
    "\n",
    "ax = plf.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                  height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.2634%</td>\n",
       "      <td>4.3887%</td>\n",
       "      <td>2.1705%</td>\n",
       "      <td>6.9871%</td>\n",
       "      <td>3.2390%</td>\n",
       "      <td>0.0791%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8377%</td>\n",
       "      <td>...</td>\n",
       "      <td>11.4508%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>14.9184%</td>\n",
       "      <td>0.1627%</td>\n",
       "      <td>6.4196%</td>\n",
       "      <td>4.0904%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.3447%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9386%</td>\n",
       "      <td>8.3625%</td>\n",
       "      <td>1.0276%</td>\n",
       "      <td>1.9641%</td>\n",
       "      <td>8.5224%</td>\n",
       "      <td>2.2393%</td>\n",
       "      <td>1.3870%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.1906%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.3545%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.4854%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.2621%</td>\n",
       "      <td>5.4660%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.4203%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.7009%</td>\n",
       "      <td>9.2088%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.6435%</td>\n",
       "      <td>9.0991%</td>\n",
       "      <td>1.8498%</td>\n",
       "      <td>1.7853%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.4004%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0757%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.0768%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.3759%</td>\n",
       "      <td>5.9712%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.8943%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.2943%</td>\n",
       "      <td>9.7508%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.2299%</td>\n",
       "      <td>9.5180%</td>\n",
       "      <td>1.4618%</td>\n",
       "      <td>2.0317%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.6643%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.7285%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.3644%</td>\n",
       "      <td>6.3487%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.4014%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.7816%</td>\n",
       "      <td>10.1712%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.7617%</td>\n",
       "      <td>9.8514%</td>\n",
       "      <td>0.8387%</td>\n",
       "      <td>2.2073%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>15.0140%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.3057%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.0554%</td>\n",
       "      <td>6.6274%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.7117%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000%  5.2634% 4.3887% 2.1705% 6.9871% 3.2390% 0.0791% 0.0000%   \n",
       "1 0.0000% 1.9386%  8.3625% 1.0276% 1.9641% 8.5224% 2.2393% 1.3870% 0.0000%   \n",
       "2 0.0000% 2.7009%  9.2088% 0.0000% 1.6435% 9.0991% 1.8498% 1.7853% 0.0000%   \n",
       "3 0.0000% 3.2943%  9.7508% 0.0000% 1.2299% 9.5180% 1.4618% 2.0317% 0.0000%   \n",
       "4 0.0000% 3.7816% 10.1712% 0.0000% 0.7617% 9.8514% 0.8387% 2.2073% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 2.8377%  ... 11.4508% 0.0000% 14.9184% 0.1627% 6.4196% 4.0904% 0.0000%   \n",
       "1 1.1906%  ... 13.3545% 0.0000%  9.4854% 0.0000% 4.2621% 5.4660% 0.0000%   \n",
       "2 0.4004%  ... 14.0757% 0.0000%  7.0768% 0.0000% 3.3759% 5.9712% 0.0000%   \n",
       "3 0.0000%  ... 14.6643% 0.0000%  4.7285% 0.0000% 2.3644% 6.3487% 0.0000%   \n",
       "4 0.0000%  ... 15.0140% 0.0000%  2.3057% 0.0000% 1.0554% 6.6274% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000%  8.3447% 0.0000%  \n",
       "1 0.0000%  9.4203% 0.0000%  \n",
       "2 0.0000%  9.8943% 0.0000%  \n",
       "3 0.0000% 10.4014% 0.0000%  \n",
       "4 0.0000% 10.7117% 0.0000%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the efficient frontier\n",
    "\n",
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "mu = port.mu # Expected returns\n",
    "cov = port.cov # Covariance matrix\n",
    "returns = port.returns # Returns of the assets\n",
    "\n",
    "ax = plf.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                       rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                       marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = plf.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Estimating Mean Risk Portfolios with Tracking Error Constraints\n",
    "\n",
    "In this part I will calculate optimal portfolios for several risk measures using a __Tracking Error Constraint respect to an Index__. First I'm going to calculate the portfolio that maximizes risk adjusted return when CVaR is the risk measure, then I'm going to calculate the portfolios that maximize the risk adjusted return for all available risk measures.\n",
    "\n",
    "### 3.1 Calculating the portfolio that maximizes Return/CVaR ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>12.3497%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.4909%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.1431%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>12.6852%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.1967%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.6775%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 0.0000% 12.3497% 0.0000% 0.0000% 7.4909% 0.0000% 5.1431%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T  \\\n",
       "weights 0.0000% 0.0000%  ... 12.6852% 0.0000% 0.0000% 0.0000% 0.0000%   \n",
       "\n",
       "             TGT     TMO     TXT      VZ    ZION  \n",
       "weights 11.1967% 0.0000% 0.0000% 3.6775% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rm = 'CVaR' # Risk measure\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plf.plot_pie(w=w, title='Sharpe Mean CVaR', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                  height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0450%</td>\n",
       "      <td>7.0613%</td>\n",
       "      <td>0.2204%</td>\n",
       "      <td>2.1297%</td>\n",
       "      <td>8.0719%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.8036%</td>\n",
       "      <td>...</td>\n",
       "      <td>6.9251%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>21.0650%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.6445%</td>\n",
       "      <td>4.1219%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>20.7635%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.2011%</td>\n",
       "      <td>5.7764%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.9135%</td>\n",
       "      <td>5.4083%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.7601%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.7028%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>14.8609%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9317%</td>\n",
       "      <td>7.3063%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>19.9810%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.8798%</td>\n",
       "      <td>4.1162%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.6360%</td>\n",
       "      <td>1.1864%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.0991%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.5624%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.6419%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.7961%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>19.1276%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.8006%</td>\n",
       "      <td>0.7004%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>12.6098%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.1936%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.3747%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.1783%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.1686%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.1508%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>17.7070%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.3932%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.4319%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0103%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>9.5697%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.4962%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.1450%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>15.5313%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 2.0450% 7.0613% 0.2204%  2.1297% 8.0719% 0.0000% 0.0000%   \n",
       "1 0.0000% 0.0000% 4.2011% 5.7764% 0.0000%  5.9135% 5.4083% 0.0000% 0.0000%   \n",
       "2 0.0000% 0.0000% 5.8798% 4.1162% 0.0000% 10.6360% 1.1864% 0.0000% 0.0000%   \n",
       "3 0.0000% 0.0000% 6.8006% 0.7004% 0.0000% 12.6098% 0.0000% 0.1936% 0.0000%   \n",
       "4 0.0000% 0.0000% 7.3932% 0.0000% 0.0000% 11.4319% 0.0000% 0.0103% 0.0000%   \n",
       "\n",
       "      JCI  ...      NI    PCAR      PSA     SEE       T      TGT     TMO  \\\n",
       "0 3.8036%  ... 6.9251% 0.0000% 21.0650% 0.0000% 2.6445%  4.1219% 0.0000%   \n",
       "1 1.7601%  ... 7.7028% 0.0000% 14.8609% 0.0000% 0.9317%  7.3063% 0.0000%   \n",
       "2 3.0991%  ... 7.5624% 0.0000% 11.6419% 0.0000% 0.0000%  6.7961% 0.0000%   \n",
       "3 0.3747%  ... 7.1783% 0.0000% 11.1686% 0.0000% 0.0000%  8.1508% 0.0000%   \n",
       "4 0.0000%  ... 9.5697% 0.0000%  6.4962% 0.0000% 0.0000% 10.1450% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000% 20.7635% 0.0000%  \n",
       "1 0.0000% 19.9810% 0.0000%  \n",
       "2 0.0000% 19.1276% 0.0000%  \n",
       "3 0.0000% 17.7070% 0.0000%  \n",
       "4 0.0000% 15.5313% 0.0000%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "\n",
    "ax = plf.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                       rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                       marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = plf.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 Calculate Optimal Portfolios for Several Risk Measures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Risk Measures available:\n",
    "#\n",
    "# 'MV': Standard Deviation.\n",
    "# 'MAD': Mean Absolute Deviation.\n",
    "# 'MSV': Semi Standard Deviation.\n",
    "# 'FLPM': First Lower Partial Moment (Omega Ratio).\n",
    "# 'SLPM': Second Lower Partial Moment (Sortino Ratio).\n",
    "# 'CVaR': Conditional Value at Risk.\n",
    "# 'EVaR': Entropic Value at Risk.\n",
    "# 'WR': Worst Realization (Minimax)\n",
    "# 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).\n",
    "# 'ADD': Average Drawdown of uncompounded cumulative returns.\n",
    "# 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'UCI': Ulcer Index of uncompounded cumulative returns.\n",
    "\n",
    "rms = ['MV', 'MAD', 'MSV', 'FLPM', 'SLPM', 'CVaR',\n",
    "       'EVaR', 'WR', 'MDD', 'ADD', 'CDaR', 'UCI', 'EDaR']\n",
    "\n",
    "w_s = pd.DataFrame([])\n",
    "\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model, rm=i, obj=obj, rf=rf, l=l, hist=hist)\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
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       "        }</style><table id=\"T_8f7db_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >MV</th>        <th class=\"col_heading level0 col1\" >MAD</th>        <th class=\"col_heading level0 col2\" >MSV</th>        <th class=\"col_heading level0 col3\" >FLPM</th>        <th class=\"col_heading level0 col4\" >SLPM</th>        <th class=\"col_heading level0 col5\" >CVaR</th>        <th class=\"col_heading level0 col6\" >EVaR</th>        <th class=\"col_heading level0 col7\" >WR</th>        <th class=\"col_heading level0 col8\" >MDD</th>        <th class=\"col_heading level0 col9\" >ADD</th>        <th class=\"col_heading level0 col10\" >CDaR</th>        <th class=\"col_heading level0 col11\" >UCI</th>        <th class=\"col_heading level0 col12\" >EDaR</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_8f7db_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "                        <td id=\"T_8f7db_row0_col0\" class=\"data row0 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col1\" class=\"data row0 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col2\" class=\"data row0 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col3\" class=\"data row0 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col4\" class=\"data row0 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col5\" class=\"data row0 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col6\" class=\"data row0 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col7\" class=\"data row0 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col8\" class=\"data row0 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col9\" class=\"data row0 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col10\" class=\"data row0 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col11\" class=\"data row0 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row0_col12\" class=\"data row0 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "                        <td id=\"T_8f7db_row1_col0\" class=\"data row1 col0\" >6.16%</td>\n",
       "                        <td id=\"T_8f7db_row1_col1\" class=\"data row1 col1\" >7.58%</td>\n",
       "                        <td id=\"T_8f7db_row1_col2\" class=\"data row1 col2\" >4.38%</td>\n",
       "                        <td id=\"T_8f7db_row1_col3\" class=\"data row1 col3\" >6.30%</td>\n",
       "                        <td id=\"T_8f7db_row1_col4\" class=\"data row1 col4\" >3.98%</td>\n",
       "                        <td id=\"T_8f7db_row1_col5\" class=\"data row1 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row1_col6\" class=\"data row1 col6\" >1.55%</td>\n",
       "                        <td id=\"T_8f7db_row1_col7\" class=\"data row1 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row1_col8\" class=\"data row1 col8\" >1.20%</td>\n",
       "                        <td id=\"T_8f7db_row1_col9\" class=\"data row1 col9\" >6.87%</td>\n",
       "                        <td id=\"T_8f7db_row1_col10\" class=\"data row1 col10\" >2.82%</td>\n",
       "                        <td id=\"T_8f7db_row1_col11\" class=\"data row1 col11\" >6.34%</td>\n",
       "                        <td id=\"T_8f7db_row1_col12\" class=\"data row1 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "                        <td id=\"T_8f7db_row2_col0\" class=\"data row2 col0\" >11.50%</td>\n",
       "                        <td id=\"T_8f7db_row2_col1\" class=\"data row2 col1\" >9.44%</td>\n",
       "                        <td id=\"T_8f7db_row2_col2\" class=\"data row2 col2\" >10.37%</td>\n",
       "                        <td id=\"T_8f7db_row2_col3\" class=\"data row2 col3\" >8.96%</td>\n",
       "                        <td id=\"T_8f7db_row2_col4\" class=\"data row2 col4\" >10.62%</td>\n",
       "                        <td id=\"T_8f7db_row2_col5\" class=\"data row2 col5\" >12.35%</td>\n",
       "                        <td id=\"T_8f7db_row2_col6\" class=\"data row2 col6\" >4.46%</td>\n",
       "                        <td id=\"T_8f7db_row2_col7\" class=\"data row2 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row2_col8\" class=\"data row2 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row2_col9\" class=\"data row2 col9\" >4.71%</td>\n",
       "                        <td id=\"T_8f7db_row2_col10\" class=\"data row2 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row2_col11\" class=\"data row2 col11\" >4.34%</td>\n",
       "                        <td id=\"T_8f7db_row2_col12\" class=\"data row2 col12\" >3.58%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "                        <td id=\"T_8f7db_row3_col0\" class=\"data row3 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col1\" class=\"data row3 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col2\" class=\"data row3 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col3\" class=\"data row3 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col4\" class=\"data row3 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col5\" class=\"data row3 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col6\" class=\"data row3 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col7\" class=\"data row3 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col8\" class=\"data row3 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col9\" class=\"data row3 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col10\" class=\"data row3 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col11\" class=\"data row3 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row3_col12\" class=\"data row3 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "                        <td id=\"T_8f7db_row4_col0\" class=\"data row4 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col2\" class=\"data row4 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col3\" class=\"data row4 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col4\" class=\"data row4 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col5\" class=\"data row4 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col6\" class=\"data row4 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col7\" class=\"data row4 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col8\" class=\"data row4 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col9\" class=\"data row4 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col10\" class=\"data row4 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col11\" class=\"data row4 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row4_col12\" class=\"data row4 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "                        <td id=\"T_8f7db_row5_col0\" class=\"data row5 col0\" >8.48%</td>\n",
       "                        <td id=\"T_8f7db_row5_col1\" class=\"data row5 col1\" >7.25%</td>\n",
       "                        <td id=\"T_8f7db_row5_col2\" class=\"data row5 col2\" >9.15%</td>\n",
       "                        <td id=\"T_8f7db_row5_col3\" class=\"data row5 col3\" >6.00%</td>\n",
       "                        <td id=\"T_8f7db_row5_col4\" class=\"data row5 col4\" >9.38%</td>\n",
       "                        <td id=\"T_8f7db_row5_col5\" class=\"data row5 col5\" >7.49%</td>\n",
       "                        <td id=\"T_8f7db_row5_col6\" class=\"data row5 col6\" >30.26%</td>\n",
       "                        <td id=\"T_8f7db_row5_col7\" class=\"data row5 col7\" >28.96%</td>\n",
       "                        <td id=\"T_8f7db_row5_col8\" class=\"data row5 col8\" >56.01%</td>\n",
       "                        <td id=\"T_8f7db_row5_col9\" class=\"data row5 col9\" >13.71%</td>\n",
       "                        <td id=\"T_8f7db_row5_col10\" class=\"data row5 col10\" >32.93%</td>\n",
       "                        <td id=\"T_8f7db_row5_col11\" class=\"data row5 col11\" >18.16%</td>\n",
       "                        <td id=\"T_8f7db_row5_col12\" class=\"data row5 col12\" >14.74%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "                        <td id=\"T_8f7db_row6_col0\" class=\"data row6 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col1\" class=\"data row6 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col2\" class=\"data row6 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col3\" class=\"data row6 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col4\" class=\"data row6 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col5\" class=\"data row6 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col6\" class=\"data row6 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col7\" class=\"data row6 col7\" >5.37%</td>\n",
       "                        <td id=\"T_8f7db_row6_col8\" class=\"data row6 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col9\" class=\"data row6 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col10\" class=\"data row6 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col11\" class=\"data row6 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row6_col12\" class=\"data row6 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "                        <td id=\"T_8f7db_row7_col0\" class=\"data row7 col0\" >3.82%</td>\n",
       "                        <td id=\"T_8f7db_row7_col1\" class=\"data row7 col1\" >2.72%</td>\n",
       "                        <td id=\"T_8f7db_row7_col2\" class=\"data row7 col2\" >1.18%</td>\n",
       "                        <td id=\"T_8f7db_row7_col3\" class=\"data row7 col3\" >2.32%</td>\n",
       "                        <td id=\"T_8f7db_row7_col4\" class=\"data row7 col4\" >0.90%</td>\n",
       "                        <td id=\"T_8f7db_row7_col5\" class=\"data row7 col5\" >5.14%</td>\n",
       "                        <td id=\"T_8f7db_row7_col6\" class=\"data row7 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row7_col7\" class=\"data row7 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row7_col8\" class=\"data row7 col8\" >13.08%</td>\n",
       "                        <td id=\"T_8f7db_row7_col9\" class=\"data row7 col9\" >1.55%</td>\n",
       "                        <td id=\"T_8f7db_row7_col10\" class=\"data row7 col10\" >0.82%</td>\n",
       "                        <td id=\"T_8f7db_row7_col11\" class=\"data row7 col11\" >1.01%</td>\n",
       "                        <td id=\"T_8f7db_row7_col12\" class=\"data row7 col12\" >8.06%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "                        <td id=\"T_8f7db_row8_col0\" class=\"data row8 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col1\" class=\"data row8 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col2\" class=\"data row8 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col3\" class=\"data row8 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col4\" class=\"data row8 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col5\" class=\"data row8 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col6\" class=\"data row8 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col7\" class=\"data row8 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col8\" class=\"data row8 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col9\" class=\"data row8 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col10\" class=\"data row8 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col11\" class=\"data row8 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row8_col12\" class=\"data row8 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "                        <td id=\"T_8f7db_row9_col0\" class=\"data row9 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col1\" class=\"data row9 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col2\" class=\"data row9 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col3\" class=\"data row9 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col4\" class=\"data row9 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col5\" class=\"data row9 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col6\" class=\"data row9 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col7\" class=\"data row9 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col8\" class=\"data row9 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col9\" class=\"data row9 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col10\" class=\"data row9 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "                        <td id=\"T_8f7db_row10_col0\" class=\"data row10 col0\" >8.63%</td>\n",
       "                        <td id=\"T_8f7db_row10_col1\" class=\"data row10 col1\" >14.80%</td>\n",
       "                        <td id=\"T_8f7db_row10_col2\" class=\"data row10 col2\" >8.82%</td>\n",
       "                        <td id=\"T_8f7db_row10_col3\" class=\"data row10 col3\" >16.70%</td>\n",
       "                        <td id=\"T_8f7db_row10_col4\" class=\"data row10 col4\" >8.46%</td>\n",
       "                        <td id=\"T_8f7db_row10_col5\" class=\"data row10 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col6\" class=\"data row10 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col7\" class=\"data row10 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col8\" class=\"data row10 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col9\" class=\"data row10 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col10\" class=\"data row10 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col11\" class=\"data row10 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row10_col12\" class=\"data row10 col12\" >6.78%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "                        <td id=\"T_8f7db_row11_col0\" class=\"data row11 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col1\" class=\"data row11 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col2\" class=\"data row11 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col3\" class=\"data row11 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col4\" class=\"data row11 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col5\" class=\"data row11 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col6\" class=\"data row11 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col7\" class=\"data row11 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col8\" class=\"data row11 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col9\" class=\"data row11 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col10\" class=\"data row11 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row11_col12\" class=\"data row11 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "                        <td id=\"T_8f7db_row12_col0\" class=\"data row12 col0\" >21.54%</td>\n",
       "                        <td id=\"T_8f7db_row12_col1\" class=\"data row12 col1\" >14.10%</td>\n",
       "                        <td id=\"T_8f7db_row12_col2\" class=\"data row12 col2\" >21.24%</td>\n",
       "                        <td id=\"T_8f7db_row12_col3\" class=\"data row12 col3\" >14.18%</td>\n",
       "                        <td id=\"T_8f7db_row12_col4\" class=\"data row12 col4\" >21.58%</td>\n",
       "                        <td id=\"T_8f7db_row12_col5\" class=\"data row12 col5\" >28.82%</td>\n",
       "                        <td id=\"T_8f7db_row12_col6\" class=\"data row12 col6\" >15.48%</td>\n",
       "                        <td id=\"T_8f7db_row12_col7\" class=\"data row12 col7\" >31.77%</td>\n",
       "                        <td id=\"T_8f7db_row12_col8\" class=\"data row12 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row12_col9\" class=\"data row12 col9\" >17.66%</td>\n",
       "                        <td id=\"T_8f7db_row12_col10\" class=\"data row12 col10\" >7.46%</td>\n",
       "                        <td id=\"T_8f7db_row12_col11\" class=\"data row12 col11\" >15.14%</td>\n",
       "                        <td id=\"T_8f7db_row12_col12\" class=\"data row12 col12\" >8.24%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "                        <td id=\"T_8f7db_row13_col0\" class=\"data row13 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col1\" class=\"data row13 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col2\" class=\"data row13 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col3\" class=\"data row13 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col4\" class=\"data row13 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col5\" class=\"data row13 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col6\" class=\"data row13 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col7\" class=\"data row13 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col8\" class=\"data row13 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col9\" class=\"data row13 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col10\" class=\"data row13 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row13_col12\" class=\"data row13 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "                        <td id=\"T_8f7db_row14_col0\" class=\"data row14 col0\" >17.59%</td>\n",
       "                        <td id=\"T_8f7db_row14_col1\" class=\"data row14 col1\" >21.37%</td>\n",
       "                        <td id=\"T_8f7db_row14_col2\" class=\"data row14 col2\" >22.47%</td>\n",
       "                        <td id=\"T_8f7db_row14_col3\" class=\"data row14 col3\" >20.90%</td>\n",
       "                        <td id=\"T_8f7db_row14_col4\" class=\"data row14 col4\" >22.75%</td>\n",
       "                        <td id=\"T_8f7db_row14_col5\" class=\"data row14 col5\" >18.64%</td>\n",
       "                        <td id=\"T_8f7db_row14_col6\" class=\"data row14 col6\" >34.22%</td>\n",
       "                        <td id=\"T_8f7db_row14_col7\" class=\"data row14 col7\" >8.89%</td>\n",
       "                        <td id=\"T_8f7db_row14_col8\" class=\"data row14 col8\" >29.71%</td>\n",
       "                        <td id=\"T_8f7db_row14_col9\" class=\"data row14 col9\" >40.09%</td>\n",
       "                        <td id=\"T_8f7db_row14_col10\" class=\"data row14 col10\" >44.96%</td>\n",
       "                        <td id=\"T_8f7db_row14_col11\" class=\"data row14 col11\" >42.31%</td>\n",
       "                        <td id=\"T_8f7db_row14_col12\" class=\"data row14 col12\" >37.10%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "                        <td id=\"T_8f7db_row15_col0\" class=\"data row15 col0\" >10.83%</td>\n",
       "                        <td id=\"T_8f7db_row15_col1\" class=\"data row15 col1\" >12.00%</td>\n",
       "                        <td id=\"T_8f7db_row15_col2\" class=\"data row15 col2\" >10.47%</td>\n",
       "                        <td id=\"T_8f7db_row15_col3\" class=\"data row15 col3\" >12.53%</td>\n",
       "                        <td id=\"T_8f7db_row15_col4\" class=\"data row15 col4\" >10.43%</td>\n",
       "                        <td id=\"T_8f7db_row15_col5\" class=\"data row15 col5\" >12.69%</td>\n",
       "                        <td id=\"T_8f7db_row15_col6\" class=\"data row15 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row15_col7\" class=\"data row15 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row15_col8\" class=\"data row15 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row15_col9\" class=\"data row15 col9\" >5.26%</td>\n",
       "                        <td id=\"T_8f7db_row15_col10\" class=\"data row15 col10\" >3.35%</td>\n",
       "                        <td id=\"T_8f7db_row15_col11\" class=\"data row15 col11\" >3.89%</td>\n",
       "                        <td id=\"T_8f7db_row15_col12\" class=\"data row15 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "                        <td id=\"T_8f7db_row16_col0\" class=\"data row16 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col1\" class=\"data row16 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col2\" class=\"data row16 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col3\" class=\"data row16 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col4\" class=\"data row16 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col5\" class=\"data row16 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col6\" class=\"data row16 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col7\" class=\"data row16 col7\" >9.39%</td>\n",
       "                        <td id=\"T_8f7db_row16_col8\" class=\"data row16 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col9\" class=\"data row16 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col10\" class=\"data row16 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col11\" class=\"data row16 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row16_col12\" class=\"data row16 col12\" >2.55%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "                        <td id=\"T_8f7db_row17_col0\" class=\"data row17 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col1\" class=\"data row17 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col2\" class=\"data row17 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col3\" class=\"data row17 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col4\" class=\"data row17 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col5\" class=\"data row17 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col6\" class=\"data row17 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col7\" class=\"data row17 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col8\" class=\"data row17 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col9\" class=\"data row17 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col10\" class=\"data row17 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col11\" class=\"data row17 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row17_col12\" class=\"data row17 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "                        <td id=\"T_8f7db_row18_col0\" class=\"data row18 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col1\" class=\"data row18 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col2\" class=\"data row18 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col3\" class=\"data row18 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col4\" class=\"data row18 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col5\" class=\"data row18 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col6\" class=\"data row18 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col7\" class=\"data row18 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col8\" class=\"data row18 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col9\" class=\"data row18 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col10\" class=\"data row18 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col11\" class=\"data row18 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row18_col12\" class=\"data row18 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "                        <td id=\"T_8f7db_row19_col0\" class=\"data row19 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col1\" class=\"data row19 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col2\" class=\"data row19 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col3\" class=\"data row19 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col4\" class=\"data row19 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col5\" class=\"data row19 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col6\" class=\"data row19 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col7\" class=\"data row19 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col8\" class=\"data row19 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col9\" class=\"data row19 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col10\" class=\"data row19 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col11\" class=\"data row19 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row19_col12\" class=\"data row19 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "                        <td id=\"T_8f7db_row20_col0\" class=\"data row20 col0\" >7.18%</td>\n",
       "                        <td id=\"T_8f7db_row20_col1\" class=\"data row20 col1\" >4.75%</td>\n",
       "                        <td id=\"T_8f7db_row20_col2\" class=\"data row20 col2\" >8.91%</td>\n",
       "                        <td id=\"T_8f7db_row20_col3\" class=\"data row20 col3\" >5.86%</td>\n",
       "                        <td id=\"T_8f7db_row20_col4\" class=\"data row20 col4\" >9.26%</td>\n",
       "                        <td id=\"T_8f7db_row20_col5\" class=\"data row20 col5\" >11.20%</td>\n",
       "                        <td id=\"T_8f7db_row20_col6\" class=\"data row20 col6\" >14.02%</td>\n",
       "                        <td id=\"T_8f7db_row20_col7\" class=\"data row20 col7\" >15.63%</td>\n",
       "                        <td id=\"T_8f7db_row20_col8\" class=\"data row20 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row20_col9\" class=\"data row20 col9\" >1.35%</td>\n",
       "                        <td id=\"T_8f7db_row20_col10\" class=\"data row20 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row20_col11\" class=\"data row20 col11\" >0.49%</td>\n",
       "                        <td id=\"T_8f7db_row20_col12\" class=\"data row20 col12\" >4.78%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "                        <td id=\"T_8f7db_row21_col0\" class=\"data row21 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col1\" class=\"data row21 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col2\" class=\"data row21 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col3\" class=\"data row21 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col4\" class=\"data row21 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col5\" class=\"data row21 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col6\" class=\"data row21 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col7\" class=\"data row21 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col8\" class=\"data row21 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col9\" class=\"data row21 col9\" >0.58%</td>\n",
       "                        <td id=\"T_8f7db_row21_col10\" class=\"data row21 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col11\" class=\"data row21 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row21_col12\" class=\"data row21 col12\" >6.05%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "                        <td id=\"T_8f7db_row22_col0\" class=\"data row22 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col1\" class=\"data row22 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col2\" class=\"data row22 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col3\" class=\"data row22 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col4\" class=\"data row22 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col5\" class=\"data row22 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col6\" class=\"data row22 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col7\" class=\"data row22 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col8\" class=\"data row22 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col9\" class=\"data row22 col9\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col10\" class=\"data row22 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col11\" class=\"data row22 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row22_col12\" class=\"data row22 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "                        <td id=\"T_8f7db_row23_col0\" class=\"data row23 col0\" >4.27%</td>\n",
       "                        <td id=\"T_8f7db_row23_col1\" class=\"data row23 col1\" >5.99%</td>\n",
       "                        <td id=\"T_8f7db_row23_col2\" class=\"data row23 col2\" >3.00%</td>\n",
       "                        <td id=\"T_8f7db_row23_col3\" class=\"data row23 col3\" >6.25%</td>\n",
       "                        <td id=\"T_8f7db_row23_col4\" class=\"data row23 col4\" >2.63%</td>\n",
       "                        <td id=\"T_8f7db_row23_col5\" class=\"data row23 col5\" >3.68%</td>\n",
       "                        <td id=\"T_8f7db_row23_col6\" class=\"data row23 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row23_col7\" class=\"data row23 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row23_col8\" class=\"data row23 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row23_col9\" class=\"data row23 col9\" >8.18%</td>\n",
       "                        <td id=\"T_8f7db_row23_col10\" class=\"data row23 col10\" >7.65%</td>\n",
       "                        <td id=\"T_8f7db_row23_col11\" class=\"data row23 col11\" >8.32%</td>\n",
       "                        <td id=\"T_8f7db_row23_col12\" class=\"data row23 col12\" >8.12%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8f7db_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "                        <td id=\"T_8f7db_row24_col0\" class=\"data row24 col0\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col1\" class=\"data row24 col1\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col2\" class=\"data row24 col2\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col3\" class=\"data row24 col3\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col4\" class=\"data row24 col4\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col5\" class=\"data row24 col5\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col6\" class=\"data row24 col6\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col7\" class=\"data row24 col7\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col8\" class=\"data row24 col8\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col9\" class=\"data row24 col9\" >0.03%</td>\n",
       "                        <td id=\"T_8f7db_row24_col10\" class=\"data row24 col10\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col11\" class=\"data row24 col11\" >0.00%</td>\n",
       "                        <td id=\"T_8f7db_row24_col12\" class=\"data row24 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fb1654f7cd0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(14)\n",
    "fig.set_figheight(6)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot.bar(ax=ax)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
